Sustainability analysis in integrated inventory control and transportation systems

Due to the importance of costs as well as environmental effects of logistical activities throughout supply chains, such as inventory holding, freight transportation, and warehousing activities, this dissertation models and analyzes four integrated inventory control and transportation problems that account for economic and environmental aspects of a supply chain agents related decisions. The first model presents an integrated inventory control and transportation problem in a single item deterministic demand setting. A supply chain agents inventory control and transportation mode selection problem is solved under carbon cap, carbon cap and trade, carbon cap and offset, and carbon tax regulations. The second model focuses on an integrated inventory control and transportation problem in a single item stochastic demand setting integrating environmental objectives into a continuous review inventory control system with considerations of two different transportation modes. The third model studies an integrated inventory control and transportation problem in a multi-item deterministic demand setting, in which, a decision making method is developed considering the economic and environmental objectives. In the fourth model, a multi-item stochastic demand consolidation policy is analyzed with the consideration of heterogeneous freight trucks for transportation. It is shown that the consolidation policy suggested can result in substantial economic as well as environmental benefits for the supply chain agents --Abstract, page iii

Assessment of joint inventory replenishment: a cooperative games approach

This research deals with the design of a logistics strategy with a collaborative approach between non-competing companies, who through joint coordination of the replenishment of their inventories reduce their costs thanks to the exploitation of economies of scale. The collaboration scope includes sharing logistic resources with limited capacities; transport units, warehouses, and management processes. These elements conform a novel extension of the Joint Replenishment Problem (JRP) named the Schochastic Collaborative Joint replenishment Problem (S-CJRP). The introduction of this model helps to increase practical elements into the inventory replenishment problem and to assess to what extent collaboration in inventory replenishment and logistics resources sharing might reduce the inventory costs. Overall, results showed that the proposed model could be a viable alternative to reduce logistics costs and demonstrated how the model can be a financially preferred alternative than individual investments to leverage resources capacity expansions. Furthermore, for a practical instance, the work shows the potential of JRP models to help decision-makers to better understand the impacts of fleet renewal and inventory replenishment decisions over the cost and CO2 emissions.DoctoradoDoctor en Ingeniería Industria

Constrained Joint Replenishment Problem with Refrigerated Vehicles

We study a constrained joint replenishment problem with a multi-commodity refrigerated road transport in cold chain logistics. Each truck may have multiple temperature zones, since products in full truckload shipment may have different temperature requirements. In the proposed mathematical programming model, we want to minimize the expected total cost that includes the inventory cost and the transportation cost as well as the penalty cost if temperature violation occurs subject to the full truckload constraint. Under the deterministic demand, the cycle time of each product, the temperature of each zone in each truck and the allocation plan (the number of units of each product to be shipped in each zone in each truck) are obtained from the mixed-integer nonlinear optimization model. Under the stochastic demand, we assume that the inventory is controlled using a periodic review system, and the order-up-to level is chosen to maintain the desired cycle service level of each product. In the case study of one of the largest modern grocery retailers in Thailand, our model is applied to obtain the optimal replenishment policy. Currently, the company's fleet consists of single-temperature trucks. We estimate the monetary benefit obtained by switching from a single-temperature truck to a multi-temperature truck. We also estimate the cost reduction from reducing the lead time. Finally, our model can be used to quantify the trade-off between the service level and the inventory cost to help the company choose the appropriate service levels

Optimization Models for Cost Efficient and Environmentally Friendly Supply Chain Management

This dissertation aims to provide models which will help companies make sustainable logistics management and transportation decisions. These models are extensions of the economic lot sizing model with the availability of multiple replenishment modes. The objective of the models is to minimize total replenishment costs and emissions. The study provides applications of these models on contemporary supply chain problems. Initially, the impact of carbon regulatory mechanisms on the replenishment decisions are analyzed for a biomass supply chain under fixed charge replenishment costs. Then, models are extended to consider multiple-setups replenishment costs for age dependent perishable products. For a cost minimization objective, solution algorithms are proposed to solve cases where one, two or multiple replenishment modes are available. Finally, using a bi-objective model, tradeoffs in costs and emissions are analyzed in a perishable product supply chain

Truckload Shipment Planning and Procurement

This dissertation presents three issues encountered by a shipper in the context of truckload transportation. In all of the studies, we utilize optimization techniques to model and solve the problems. Each study is inspired from the real world and much of the data used in the experiments is real data or representative of real data. The first topic is about the freight consolidation in truckload transportation. We integrate it with a purchase incentive program to increase truckload utilization and maximize profit. The second topic is about supporting decision making collaboration among departments of a manufacturer. It is a bi-objective optimization model. The third topic is about procurement in an adverse market. We study a modification of the existing procurement process to consider the market stochastic into marking decisions. In all three studies, our target is to develop effectively methodologies to seek optimal answers within a reasonable amount of time

Energy and Carbon Dioxide Impacts from Lean Logistics and Retailing Systems: A Discrete-event Simulation Approach for the Consumer Goods Industry

abstract: Consumer goods supply chains have gradually incorporated lean manufacturing principles to identify and reduce non-value-added activities. Companies implementing lean practices have experienced improvements in cost, quality, and demand responsiveness. However certain elements of these practices, especially those related to transportation and distribution may have detrimental impact on the environment. This study asks: What impact do current best practices in lean logistics and retailing have on environmental performance? The research hypothesis of this dissertation establishes that lean distribution of durable and consumable goods can result in an increased amount of carbon dioxide emissions, leading to climate change and natural resource depletion impacts, while lean retailing operations can reduce carbon emissions. Distribution and retailing phases of the life cycle are characterized in a two-echelon supply chain discrete-event simulation modeled after current operations from leading organizations based in the U.S. Southwest. By conducting an overview of critical sustainability issues and their relationship with consumer products, it is possible to address the environmental implications of lean logistics and retailing operations. Provided the waste reduction nature from lean manufacturing, four lean best practices are examined in detail in order to formulate specific research propositions. These propositions are integrated into an experimental design linking annual carbon dioxide equivalent emissions to: (1) shipment frequency between supply chain partners, (2) proximity between decoupling point of products and final customers, (3) inventory turns at the warehousing level, and (4) degree of supplier integration. All propositions are tested through the use of the simulation model. Results confirmed the four research propositions. Furthermore, they suggest synergy between product shipment frequency among supply chain partners and product management due to lean retailing practices. In addition, the study confirms prior research speculations about the potential carbon intensity from transportation operations subject to lean principles.Dissertation/ThesisPh.D. Sustainability 201

Design of a network of reusable logistic containers

In this paper, we consider the management of the return flows of empty logistic containers that accumulate at the customer’s sites. These containers must be brought back to the factories in order to sustain future expeditions. We consider a network composed of several factories and several customers in which the return flows are independent of the delivery flows. The models and their solutions aim at finding to which factory the contain- ers have to be brought back and at which frequency. These frequencies directly define the volume of logistic containers to hold in the network. We consider fixed transportation costs depending on the locations of the customers and of the factories and linear holding costs for the inventory of logistic containers. The analysis also provides insight on the benefit of pooling the containers among different customers and/or factories.supply chain management, returnable items, reverse logistic, economic order quantity, network design

Estimation and Allocation of Cost Savings from Collaborations

학위논문(석사) -- 서울대학교대학원 : 공과대학 산업공학과, 2021.8. 문일경.The physical internet (PI) is a state-of-the-art open global supply chain network that is gaining attention from both participants and researchers of supply chains. The PI uses standardized containers to dispatch shipments through an interconnected network within a supply chain, where information, storage facilities, and transportation methods are shared participants of the physical internet. The network aims to save costs, handle volatile demand and information, and be socially and environmentally responsible. Up until now, however, almost all studies concerning the PI have focused primarily on its conceptual development and the advantages of putting it into practical, widespread use. Studies that consider realistic constraints of its use, such as empty runs of transportation, limited capacity of resources, or an equitable allocation of the cost savings obtained from its implementation are limited. While in general the PI can offer greater efficiency and sustainability compared to the traditional supply chain network, in certain situations some users of it experience loss through its use because of the inherent setup it presents of sharing capacitated resources. Therefore, compensating companies that experience loss when joining a PI is essential in building a solid network. In this thesis, in order to address the minimization of a total cost problem in the production-inventory-distribution decision of a PI, we first propose a mixed-integer linear programming (MILP) model formulation that takes into account capacitated factory and warehouse capacity, the penalty sustained by empty runs of transportation, and the maximum delivery distance of freight runs. Next, we use the model to compare the costs incurred by individual players when they do not participate in the PI and the costs of collaboration in the PI in which players do participate. After comparing the costs saved by participating in the PI, we then allocated the cost savings among independent supply chains, allotting them through three different allocation methods, including the Shapley value method, which is a cooperative game theory solution method.피지컬 인터넷은 최첨단의 공유 글로벌 공급망 네트워크로 다양한 학자 및 실무자들의 관심을 끌고 있습니다. 피지컬 인터넷은 표준화된 컨테이너를 이용하여 상호 연결된 네트워크를 통해 제품 및 재화를 발송합니다. 이 때, 정보, 보관 시설 및 운송 수단은 참여자들 간에 공유됩니다. 이 네트워크는 비용을 절감하고 변동성이 큰 수요와 정보를 처리하고 사회적, 환경적으로 지속가능성을 유지하는 것을 목표로 합니다. 지금까지 피지컬 인터넷에 대한 연구는 주로 그 개념과 프레임워크의 개발, 그리고 사회에 도입하였을 때의 장점을 주로 다루었습니다. 피지컬 인터넷 속에서 운송 수단의 공차 운행, 자원의 한계 용량, 절감한 비용의 배분 등과 같은 현실적인 요소들에 대한 고려를 한 연구들은 아직 제한적입니다. 피지컬 인터넷은 전체적으로 보았을 때 기존의 공급망에 비해 더 큰 효율성과 지속 가능성을 얻을 수 있지만 특정한 상황에서는 일부 참가자는 현실적인 제약 상황으로 인해 오히려 손해를 보는 경우가 존재할 수 있습니다. 따라서 더 큰 효율성과 지속 가능성을 얻을 수 있는 피지컬 인터넷에 기업들을 참여시키기 위해선 그들이 참여함으로써 손해를 보는 상황을 만들지 않는 것이 필수적인 조건입니다. 본 논문에서는 먼저 운송 수단의 공차 운행 페널티 비용, 최대 운송 가능 거리, 창고의 폐쇄를 고려한 통합 생산-재고-물류 최소 비용 혼합 정수 선형 계획법 모형을 제안하였습니다. 그 후, 개별적인 공급망의 비용과 피지컬 인터넷 하에서 협업한 통합 공급망의 비용을 비교하여 비용 절감 효과를 계산한 후 협력 게임의 일종인 섀플리 값을 포함한 세 가지 배분 방법을 통해 비용 절감 효과 배분을 살펴보았습니다.Chapter 1 Introduction 1 Chapter 2 Literature Review 5 2.1 The Physical Internet 5 2.2 Cost Savings Allocation Problem 8 Chapter 3 Model Formulation 10 3.1 Problem Definition 10 3.2 Assumptions 15 3.3 Notaions and Formulations 17 Chapter 4 Numerical Analysis of the MILP model 22 4.1 Experimental Design 22 4.2 Results Analysis 26 4.3 Cost Parameter Sensitivity Analysis 29 Chapter 5 Cost Savings Allocation Problem 31 5.1 No Pre-set Rules 31 5.2 Proportional to Customer Demand 33 5.3 The Shapley Value 35 Chapter 6 Conclusions 37 Bibliography 39 국문초록 42석

Resource allocation in service and logistics systems

Resource allocation is a problem commonly encountered in strategic planning, where a typical objective is to minimize the associated cost or maximize the resulting profit. It is studied analytically and numerically for service and logistics systems in this dissertation, with the major resource being people, services or trucks. First, a staffing level problem is analyzed for large-scale single-station queueing systems. The system manager operates an Erlang-C queueing system with a quality-of-service (QoS) constraint on the probability that a customer is queued. However, in this model, the arrival rate is uncertain in the sense that even the arrival-rate distribution is not completely known to the manager. Rather, the manager has an estimate of the support of the arrival-rate distribution and the mean. The goal is to determine the number of servers needed to satisfy the quality of service constraint. Two models are explored. First, the constraint is enforced on an overall delay probability, given the probability that different feasible arrival-rate distributions are selected. In the second case, the constraint has to be satisfied by every possible distribution. For both problems, asymptotically optimal solutions are developed based on Halfin-Whitt type scalings. The work is followed by a discussion on solution uniqueness with a joint QoS constraint and a given arrival-rate distribution in multi-station systems. Second, an extension to Naor’s analysis on the joining or balking problem in observable M=M=1 queues and its variant in unobservable M=M=1 queues is presented to incorporate parameter uncertainty. The arrival-rate distribution is known to all, but the exact arrival rate is unknown in both cases. The optimal joining strategies are obtained and compared from the perspectives of individual customers, the social optimizer and the profit maximizer, where differences are recognized between the results for systems with deterministic and stochastic arrival rates. Finally, an integrated ordering and inbound shipping problem is formulated for an assembly plant with a large number of suppliers. The objective is to minimize the annual total cost with a static strategy. Potential transportation modes include full truckload shipping and less than truckload shipping, the former of which allows customized routing while the latter does not. A location-based model is applied in search of near-optimal solutions instead of an exact model with vehicle routing, and numerical experiments are conducted to investigate the insights of the problem.Operations Research and Industrial Engineerin

Essays in Measuring, Controlling, and Coordinating Supply Chain Inventory and Transportation Operations

Supply chain collaboration programs, such as continuous replenishment program (CRP), is among the most popular supply chain management practices. CRP is an arrangement between two partners in a supply chain to share information on a regular basis for lowering logistics costs while maintaining or increasing service levels. CRP shifts the replenishment responsibility to the upstream partner to avoid the bullwhip effect across the supply chain. This dissertation aims to quantify, measure, and expand the benefits of CRP for the purpose of reducing logistics cost and improving customer service. The developed models in this dissertation are all applied in different case studies supported by a group of major healthcare partners. The first research contribution, discussed in chapter 2, is a comprehensive data-driven cost approximation model that quantifies the benefits of CRP for both partners under three cost components of inventory holding, transportation and ordering processing without imposing assumptions that normally do not hold in practice. The second contribution, discussed in chapter 3, is development of a verifiable efficiency measurement system to ensure the benefits of CRP for all partners. Multi-functional efficiency metrics are designed to capture the trade-off in gaining efficiency between multiple functions of logistics (i.e. inventory efficiency, transportation efficiency, and order processing efficiency). In addition, a statistical process control (SPC) system is developed to monitor the metrics over time. We discuss suitable SPC systems for various time series behaviors of the metrics. The third contribution of the dissertation, discussed in chapter 4, is development of a multi-objective decision analysis (MODA) model for multi-stop truckload (MSTL) planning. MSTL is becoming increasing popular among shippers while is experiencing significant resistance from carriers. MSTL is capable of reducing the shipping cost of shippers substantially but it can also disrupt carriers’ operations. A MODA model is developed for this problem to incorporate the key decision criteria of both sides for identifying the most desirable multi-stop routes from the perspective both decision makers